Data mining is a foundational piece of the data analytics skill set. At a high level, it allows the analyst to discover patterns in data, and transform it into a usable product. The course will teach data mining algorithms for analyzing very large data sets. It will have an applied focus, in that it is meant for preparing students to utilize topics in data mining to solve real world problems
These following code are my homework source code.
| No. | Main Application | Programming | Tags | Score |
|---|---|---|---|---|
| 1 | Data Exploration | Python | MapReduce Spark Pyspark |
8.0 (python) + 0.0 (scala) / 8.0 + 0.8 |
| 2 | Find Frequent Itemsets | Python | PCY Apriori SON |
8.0 (python) + 0.0 (scala) / 8.0 + 0.8 |
| 3 | Recommendation Systems | Python | Collaborative Filtering MinHash LSH |
8.0 (python) + 0.0 (scala) / 8.0 + 0.8 |
| 4 | Graph Network Algorithm | Python | Betweenness Communities Detection Girvan-Newman Algorithm |
6.5 (python) + 0.0 (scala) / 8.0 + 0.8 |
| 5 | Clustering Algorithm | Python | K-Means Bradley-Fayyad-Reina (BFR) Algorithm NMI |
8.0 (python) + 0.0 (scala) / 8.0 + 0.8 |
| 6 | Streaming Mining | Python | Bloom Filter Flajolet-Martin Algorithm Twitter Streaming Reservoir Sampling |
8.0 (python) + 0.0 (scala) / 8.0 + 0.8 |
| - | Hybrid Recommendation System | Code | User Based Collaborative Filtering Baseline Switching Cascade User Graph |
RMSE: 1.18 |